2020
Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes
Kilian Kleeberger, Markus Völk, Marius Moosmann, Erik Thiessenhusen, Florian Roth, Richard Bormann +1
IROS 2020poster
In this paper, we introduce a novel learning-based approach for grasping known rigid objects in highly cluttered scenes and precisely placing them based on depth images. Our Placement Quality Network (PQ-Net) estimates the object pose and the quality for each automatically generated grasp pose for m…